CN109856080B - Near-infrared multispectral imaging multi-index collaborative nondestructive evaluation method for freshness of fish fillet - Google Patents
Near-infrared multispectral imaging multi-index collaborative nondestructive evaluation method for freshness of fish fillet Download PDFInfo
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Abstract
The invention discloses a multispectral multi-index synergistic fillet freshness degree evaluation method which is used for respectively measuring freshness indexes TVB-N value, TBARS value and K value of fillet samples refrigerated for different days; scanning corresponding fish slice samples by using a multispectral imaging system to obtain corresponding multispectral images, processing the near-infrared multispectral images, and respectively extracting 5 average reflection spectrum values corresponding to the central wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890 nm; and establishing a prediction model by using an LS-SVM (least squares-support vector machine) based on the acquired TVB-N value, TBARS value, K value and average spectrum value, and predicting the freshness of the fillet sample to be detected. The invention adopts multispectral multi-index to cooperatively evaluate the freshness of the fillets, reduces the time required by the traditional method, enhances the detection efficiency and the accuracy, and can effectively realize the purposes of quick, nondestructive and non-contact online detection.
Description
Technical Field
The invention relates to the field of fillet freshness quality detection, in particular to a nondestructive evaluation method for fillet freshness through near-infrared multispectral imaging and multi-index cooperation.
Background
Fish is an important component of aquatic products. The fish meat has delicious taste and high content of nutrient substances, is an important source of nutrient substances such as protein, amino acid, fat and the like required by human beings, and is an important component of human diet. Freshness is an important comprehensive index for fish meat quality evaluation. Factors affecting the freshness of fish meat are many, and mainly relate to storage temperature, microbial contamination, processing method and physical-chemical and biochemical changes of the processing method.
At present, methods for measuring and evaluating freshness of fish meat are roughly divided into: sensory evaluation, physical property measurement, chemical analysis, and the like. The freshness of fish meat is evaluated by measuring the values of protein degradation index-volatile basic nitrogen value (TVB-N), fat oxidation index-thiobarbituric acid value (TBARS) and ATP degradation index-K by a chemical analysis method commonly used in laboratories. Generally speaking, when the TVB-N value is less than or equal to 15mg N/100g is defined as primary freshness, the TVB-N value is less than or equal to 20mg N/100g and is less than or equal to 15mg N/100g, the TVB-N value is greater than 20mg N/100g, the edible value is defined as lost; similarly, when the K value is less than or equal to 20 percent, the fish meat is judged to be first-grade fresh; when the K value is more than 20% and less than or equal to 60%, the fish meat is judged to be second-level fresh and still can be eaten; when the K value is more than 60 percent, the fish meat is rotten and deteriorated and loses the edible value. The corresponding three indexes are usually measured in a laboratory by adopting a semimicro azotometry method, a spectrophotometry method and a high performance liquid chromatography method. Although the result of the chemical analysis method test is accurate, the chemical analysis method test belongs to destructive detection. Obviously, in the actual detection process, the methods have the defects of complicated steps, high operation requirement, time and labor consumption and incapability of realizing nondestructive rapid online detection.
Disclosure of Invention
In order to overcome the defects and shortcomings in the prior art, the invention aims to provide a nondestructive evaluation method for fillet freshness by near-infrared multispectral imaging multi-index cooperation, which can effectively save detection time, save measurement cost and realize rapid nondestructive detection and evaluation of fillet freshness on the premise of not damaging fillet samples.
The purpose of the invention is realized by the following technical scheme:
the nondestructive evaluation method for the freshness of the fillets with near-infrared multispectral imaging and multi-index cooperation comprises the following steps:
(1) from 0 day, every 1 or 2 days, preparing fish samples and refrigerating for different days, wherein the longest refrigerating day is not more than 7 days, and obtaining N fish slice samples which are randomly divided into M groups; n is greater than 90, M is an integer from 4 to 10; the number of each group of samples is N/5;
(2) scanning the fillet samples with different storage days by using a near-infrared multispectral imaging system to obtain multispectral images of N fillet samples;
(3) extracting reflection spectrum values corresponding to multispectral central wavelengths of the fish slice sample, wherein the central wavelengths are 1250nm, 1452nm, 1655nm, 1785nm and 1890nm respectively;
(4) measuring three indexes representing the freshness of the fish fillets, measuring a TVB-N value by using a semi-micro azotometry, measuring a TBARS value by using a spectrophotometry and measuring a K value by using a high performance liquid chromatography;
(5) combining the reflection spectrum value corresponding to the central wavelength obtained in the step (3) and three fillet freshness index values of the TVB-N value, the TBARS value and the K value obtained in the step (4), and constructing a fillet freshness multi-index prediction model by using a least square support vector machine (LS-SVM); y isi＝C0+AX1250nm+BX1452nm+CX1655nm+DX1785nm+EX1890nm；
Wherein, YiThe index TVB-N value, TBARS value and K value are freshness evaluation indexes, i is a freshness grade, the values are 1, 2 and 0 respectively, and the first-level freshness, the second-level freshness and the no-freshness are respectively represented; x1250nm、X1452nm、X1655nm、X1785nm、X1890nmAverage reflectance spectrum values corresponding to wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890nm respectively, and corresponding to spectrum values at the time of measurement of TVB-N value, TBARS value and K value; c0A, B, C, D, E are coordination coefficients which are automatically generated through Matlab programming;
(6) and (5) evaluating the freshness of the fillet sample to be tested by using the prediction model obtained in the step (5).
To further achieve the object of the present invention, preferably, the freshness evaluation in step (6) is:
when the fillets are in first-grade freshness, the model YiThe coordination coefficients are respectively C0-22.31, a ═ 25.23, B ═ 21.42, C ═ 46.55, D ═ 124.12, E ═ 23.48; the variation ranges of the three indexes measured simultaneously are respectively as follows: the TVB-N value is less than or equal to 14.27mg N/100g, the TBARS value is less than or equal to 0.58mg/kg, and the K value is less than or equal to 19.36 percent;
when the fillet is in the second-level freshness degree, the model YiThe coordination coefficients are respectively C0-103.77, a 35.64, B41.72, C32.11, D165.69, E221.53; the variation ranges of the three indexes measured simultaneously are respectively as follows: the TVB-N value is more than 14.27mgN/100g and less than or equal to 19.88mg N/100g, the TBARS value is more than 0.58mg/kg and less than or equal to 0.99mg/kg, and the K value is more than 19.36 percent and less than or equal to 59.48 percent;
when the fillet is at non-freshness, the model YiThe coordination coefficients are respectively C0-202.8, a-32.37, B-46.42, C-41.7, D-195.13, e-213.8; the variation ranges of the three indexes measured simultaneously are respectively as follows: TVB-N value is more than 19.88mgN/100g, TBARS value is more than 0.99mg/kg, and K value is more than 59.48%.
Preferably, the extracting of the reflectance spectrum value corresponding to the multispectral center wavelength of the fillet sample in the step (3) is performed after size correction, masking and denoising of the obtained multispectral image of the fillet sample.
Preferably, the fish of the fish sample in step (1) is grass carp, silver carp, big head fish or black carp.
Preferably, the preparation of the fish meat sample in the step (1) comprises the steps of scaling, removing internal organs, removing heads, removing tails and skins, and dividing into 3cm × 3cm × 1cm in size; washing with flowing water, sucking residual water on the surface of fish meat with absorbent paper, sealing in polyethylene freshness protection package, and refrigerating at 4 deg.C.
Preferably, each group of the M groups in step (1) has the same number of samples or differs by one.
Preferably, M in step (1) is 5.
The invention loses the edible value when the fillet is in the non-freshness state.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1) the method realizes the rapid nondestructive detection and evaluation of the freshness of the fillets on the premise of not damaging the fish sample, and compared with the conventional evaluation method, the method is simple and convenient to operate, rapid, nondestructive and non-contact, does not need to carry out pretreatment on the sample, and can realize the rapid nondestructive online monitoring of the freshness of the fillets.
2) The prediction model established by the invention simultaneously measures and analyzes the three index values of the freshness, so that the evaluation of the freshness is more accurate, the error is smaller, and the prediction model has direct practical significance for ensuring the fish meat quality safety and maintaining the health of consumers.
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FIG. 1 is a flow chart of a nondestructive evaluation method for fillet freshness by near-infrared multispectral imaging multi-index cooperation.
Detailed Description
For a better understanding of the present invention, the present invention will be further described with reference to the accompanying drawings and examples, but the embodiments of the present invention are not limited thereto.
Examples
As shown in fig. 1, the near-infrared multispectral imaging multi-index collaborative fillet freshness nondestructive evaluation method comprises the following steps:
(1) preparing and refrigerating grass carp fillet samples to obtain fillet samples with different refrigerating days: killing 10 grass carps (the mass is about 2kg), removing scales, viscera, heads, tails and skins, then dividing the grass carps into 200 fillet samples with similar sizes (3cm multiplied by 1cm), washing the fillet samples with flowing water, sucking residual water on the surfaces of the fillets by using absorbent paper, filling the fillets into polyethylene freshness protection bags, sealing the fillets, refrigerating the fillets for 0, 2, 4 and 6 days at 4 ℃, dividing the fillets into four groups, and randomly selecting 50 fillets in each group as the fillet samples;
(2) scanning the fillet samples at different refrigeration times by using a near-infrared multispectral imaging system (DL-604M) to obtain multispectral images of 200 fillet samples;
(3) carrying out size correction, masking and denoising on the obtained multispectral images of 200 fish fillet samples, and respectively extracting corresponding average reflection spectrum values of 5 central wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890 nm;
(4) respectively measuring TVB-N value, TBARS value and K value by high performance liquid chromatography by using a half-trace nitrogen determination method, spectrophotometry and linear transformation on 200 fillet samples, and normalizing the three index values by using a linear transformation method, wherein the measurement results are shown in Table 1;
TABLE 1TVB-N value, TBA value and K value test result condition table
(5) And (4) combining the average reflection spectrum value corresponding to the central wavelength obtained in the step (3) and the normalization values of the three indexes obtained in the step (4), and constructing a fillet freshness multi-index prediction model by using a least square support vector machine (LS-SVM):
Yi＝C0+AX1250nm+BX1452nm+CX1655nm+DX1785nm+EX1890nm；
wherein, YiThe index TVB-N value, TBARS value and K value are freshness evaluation indexes, i is a freshness grade, the values are 1, 2 and 0 respectively, and the first-level freshness, the second-level freshness and the no-freshness are respectively represented; x1250nm、X1452nm、X1655nm、X1785nm、X1890nmAverage reflectance spectrum values corresponding to wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890nm respectively, and corresponding to spectrum values at the time of measurement of TVB-N value, TBARS value and K value; c0A, B, C, D, E are coordination coefficients which are automatically generated through Matlab programming;
when the fillets are in first-grade freshness, the model YiThe coordination coefficients are respectively C0-22.31, a ═ 25.23, B ═ 21.42, C ═ 46.55, D ═ 124.12, E ═ 23.48; the variation ranges of the three indexes measured simultaneously are respectively as follows: the TVB-N value is less than or equal to 14.27mg N/100g, the TBARS value is less than or equal to 0.58mg/kg, and the K value is less than or equal to 19.36 percent;
when the fillet is in the second-level freshness degree, the model YiThe coordination coefficients are respectively C0-103.77, a 35.64, B41.72, C32.11, D165.69, E221.53; the variation ranges of the three indexes measured simultaneously are respectively as follows: the TVB-N value is more than 14.27mgN/100g and less than or equal to 19.88mg N/100g, the TBARS value is more than 0.58mg/kg and less than or equal to 0.99mg/kg, and the K value is more than 19.36 percent and less than or equal to 59.48 percent;
model Y when the fillet is at zero freshness (loss of eating value)iThe coordination coefficients are respectively C0-202.8, a-32.37, B-46.42, C-41.7, D-195.13, e-213.8; the variation ranges of the three indexes measured simultaneously are respectively as follows: TVB-N value is more than 19.88mg N/100g, TBARS value is more than 0.99mg/kg, and K value is more than 59.48%.
(6) And (5) evaluating the freshness of the fillet sample to be tested by using the prediction model obtained in the step (5).
In the embodiment, the TVB-N value, TBARS value and K value of the grass carp fillet sample refrigerated for 2 days, which are obtained by prediction through the constructed model, and the TVB-N value, the TBARS value and the K value which are obtained by respectively adopting a half-micro azotometry method, a spectrophotometry method and a high performance liquid chromatography by utilizing a traditional method are shown in Table 2, the fillet is in a first-level freshness grade, experimental data obtained by the two methods are not different, the new method can be used for evaluating the freshness of the fillet instead of the traditional method, the three indexes are not different in measurement, the three indexes can be used for comprehensively evaluating the freshness of the fillet, and the evaluation is more accurate and more reliable than the evaluation of a single index.
TABLE 2 comparison of the measured values of the novel process according to the example with the conventional measuring methods (Cold storage for 2 days)
Example 2
The nondestructive evaluation method for the freshness of the fillets with near-infrared multispectral imaging and multi-index cooperation comprises the following steps:
(1) preparing big-head fillet samples and refrigerating to obtain fillet samples with different refrigerating days: killing 8 big head fishes (with the mass of about 2kg), scaling, removing internal organs, removing heads, tails and skins, then dividing the big head fishes into 160 fish slice samples with similar sizes (3cm multiplied by 1cm), washing the fish slice samples with flowing water, sucking residual water on the surfaces of the fish slices by using absorbent paper, filling the fish slice samples into polyethylene freshness protection bags, sealing the fish slice samples, refrigerating the fish slice samples for 0, 1, 3 and 5 days at the temperature of 4 ℃, dividing the fish slice samples into four groups, and randomly selecting 40 fish slices from each group as the fish slice samples;
(2) scanning the fillet samples at different refrigeration times by using a near-infrared multispectral imaging system (DL-604M) to obtain multispectral images of 160 fillet samples;
(3) carrying out size correction, masking and denoising on the obtained multispectral images of 160 fish fillet samples, and respectively extracting corresponding average reflection spectrum values of 5 central wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890 nm;
(4) respectively measuring TVB-N value by using a semi-trace azotometry, TBARS value by using a spectrophotometry and K value by using a high performance liquid chromatography, and normalizing the three index values, wherein the measurement results are shown in Table 3;
TABLE 3 results of TVB-N, TBA and K values measurements using conventional methods
(5) Combining the average reflection spectrum value corresponding to the central wavelength obtained in the step (3) and the normalization values of the three indexes obtained in the step (4), and constructing a fillet freshness multi-index prediction model by using a least square support vector machine (LS-SVM);
the prediction model in the step (5) has a model equation specifically as follows:
Yi＝C0+AX1250nm+BX1452nm+CX1655nm+DX1785nm+EX1890nm；
wherein, YiThe index TVB-N value, TBARS value and K value are freshness evaluation indexes, i is a freshness grade, the values are 1, 2 and 0 respectively, and the first-level freshness, the second-level freshness and the no-freshness are respectively represented; x1250nm、X1452nm、X1655nm、X1785nm、X1890nmAverage reflectance spectrum values corresponding to wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890nm respectively, and corresponding to spectrum values at the time of measurement of TVB-N value, TBARS value and K value; c0A, B, C, D, E are coordination coefficients which are automatically generated through Matlab programming;
when the fillets are in first-grade freshness, the model YiThe coordination coefficients are respectively C0-22.31, a ═ 25.23, B ═ 21.42, C ═ 46.55, D ═ 124.12, E ═ 23.48; the variation ranges of the three indexes measured simultaneously are respectively as follows: the TVB-N value is less than or equal to 14.27mg N/100g, the TBARS value is less than or equal to 0.58mg/kg, and the K value is less than or equal to 19.36 percent;
when the fillet is in the second-level freshness degree, the model YiThe coordination coefficients are respectively C0-103.77, a 35.64, B41.72, C32.11, D165.69, E221.53; the variation ranges of the three indexes measured simultaneously are respectively as follows: 14.27mgN/100g < TVB-N value less than or equal to 19.88mg N100g, TBARS value more than 0.58mg/kg and less than or equal to 0.99mg/kg, K value more than 19.36 percent and less than or equal to 59.48 percent;
model Y when the fillet is at zero freshness (loss of eating value)iThe coordination coefficients are respectively C0-202.8, a-32.37, B-46.42, C-41.7, D-195.13, e-213.8; the variation ranges of the three indexes measured simultaneously are respectively as follows: TVB-N value is more than 19.88mg N/100g, TBARS value is more than 0.99mg/kg, and K value is more than 59.48%.
(6) And (5) evaluating the freshness of the fillet sample to be tested by using the prediction model obtained in the step (5).
In the embodiment, the TVB-N value, TBARS value and K value of the grass carp fillet sample refrigerated for 5 days, which are obtained by the constructed model prediction, and the TVB-N value, TBARS value and K value which are obtained by the conventional method and are respectively determined by a semi-micro azotometry method, a spectrophotometry method and a high performance liquid chromatography are shown in table 4, the fillet is in a secondary freshness grade, experimental data obtained by the two methods are not different, the novel method can be used for evaluating the freshness of the fillet instead of the conventional method, the three indexes are not different in measurement, the three indexes can be used for comprehensively evaluating the freshness of the fillet, and the evaluation is more accurate and more reliable than the evaluation of a single index.
TABLE 4 comparison of the measured values of the novel process according to the examples with the conventional measuring methods (5 days of refrigeration)
The embodiments of the present invention are not limited to the embodiments described above, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and they are included in the scope of the present invention.
Claims (4)
1. The nondestructive evaluation method for the freshness of the fillets with near-infrared multispectral imaging and multi-index cooperation is characterized by comprising the following steps of:
(1) from 0 day, every 1 or 2 days, preparing fish samples and refrigerating for different days, wherein the longest refrigerating day is not more than 7 days, and obtaining N fish slice samples which are randomly divided into 5 groups; n is more than 90, and the number of samples in each group is N/5;
(2) scanning the fillet samples with different storage days by using a near-infrared multispectral imaging system to obtain multispectral images of N fillet samples;
(3) extracting reflection spectrum values corresponding to multispectral central wavelengths of the fish slice sample, wherein the central wavelengths are 1250nm, 1452nm, 1655nm, 1785nm and 1890nm respectively;
(4) measuring three indexes representing the freshness of the fish fillets, measuring a TVB-N value by using a semi-micro azotometry, measuring a TBARS value by using a spectrophotometry and measuring a K value by using a high performance liquid chromatography;
(5) combining the reflection spectrum value corresponding to the central wavelength obtained in the step (3) and three fillet freshness index values of the TVB-N value, the TBARS value and the K value obtained in the step (4), and constructing a fillet freshness multi-index prediction model by using a least square support vector machine; y isi=C0+AX1250nm+BX1452nm+CX1655nm+DX1785nm+EX1890nm；
Wherein, YiThe index TVB-N value, TBARS value and K value are freshness evaluation indexes, i is a freshness grade, the values are 1, 2 and 0 respectively, and the first-level freshness, the second-level freshness and the no-freshness are respectively represented; x1250nm、X1452nm、X1655nm、X1785nm、X1890nmAverage reflectance spectrum values corresponding to wavelengths of 1250nm, 1452nm, 1655nm, 1785nm and 1890nm respectively, and corresponding to spectrum values at the time of measurement of TVB-N value, TBARS value and K value; c0A, B, C, D, E are coordination coefficients which are automatically generated through Matlab programming;
(6) evaluating the freshness degree of the fillet sample to be tested by using the prediction model obtained in the step (5);
the freshness was evaluated as:
when the fillets are in first-grade freshness, the model YiThe coordination coefficients are respectively C0= 22.31, a =25.23, B = -21.42, C =46.55, D =124.12, E = 23.48; the variation range of three indexes measured simultaneouslyRespectively, the following steps: the TVB-N value is less than or equal to 14.27mgN/100g, the TBARS value is less than or equal to 0.58mg/kg, and the K value is less than or equal to 19.36 percent;
when the fillet is in the second-level freshness degree, the model YiThe coordination coefficients are respectively C0= 103.77, a =35.64, B =41.72, C =32.11, D =165.69, E = 221.53; the variation ranges of the three indexes measured simultaneously are respectively as follows: the TVB-N value is more than 14.27mg N/100g and less than or equal to 19.88mg N/100g, the TBARS value is more than 0.58mg/kg and less than or equal to 0.99mg/kg, and the K value is more than 19.36 percent and less than or equal to 59.48 percent;
when the fillet is at non-freshness, the model YiThe coordination coefficients are respectively C0= 202.8, a = 32.37, B =46.42, C =41.7, D =195.13, e = 213.8; the variation ranges of the three indexes measured simultaneously are respectively as follows: TVB-N value is more than 19.88mg N/100g, TBARS value is more than 0.99mg/kg, and K value is more than 59.48%.
2. The near-infrared multispectral imaging multiindex collaborative fillet freshness nondestructive evaluation method according to claim 1, wherein the extraction of the reflectance spectrum value corresponding to the multispectral center wavelength of the fillet sample in the step (3) is performed after size correction, masking and denoising of the obtained multispectral image of the fillet sample.
3. The near-infrared multispectral imaging multi-index collaborative fish slice freshness nondestructive evaluation method according to claim 1, wherein the fish of the fish sample in the step (1) is grass carp, silver carp, big head fish or black carp.
4. The near-infrared multispectral imaging multiindex coordinated fillet freshness nondestructive evaluation method according to claim 1, wherein the preparation of the fish meat sample in the step (1) comprises scaling, eviscerating, decapitating and skinning, and the fish meat sample is divided into 3cm x 1cm in size; washing with flowing water, sucking residual water on the surface of fish meat with absorbent paper, sealing in polyethylene freshness protection package, and refrigerating at 4 deg.C.
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